Libraries

library(readr) # Read/write data files
library(ggplot2)  # For all the badass plots
Use suppressPackageStartupMessages() to eliminate package startup messages
library(skimr)  # For best data summarize
library(TSstudio)

Create the dataframe

path <- "../data/temixco.csv"
data_temixco <- read_csv(path)
Rows: 52560 Columns: 8
── Column specification ─────────────────────────────────────────────────────────────────────────────────────────
Delimiter: ","
dbl  (7): Ib, Ig, To, RH, WS, WD, P
dttm (1): time

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
data_temixco

Summary of the data

summary(data_temixco)
      time                           Ib                 Ig                 To              RH        
 Min.   :2018-01-01 00:00:00   Min.   :   0.000   Min.   :   0.000   Min.   : 8.16   Min.   : 5.648  
 1st Qu.:2018-04-02 05:57:30   1st Qu.:   0.001   1st Qu.:   0.000   1st Qu.:19.35   1st Qu.:29.770  
 Median :2018-07-02 11:55:00   Median :   0.260   Median :   3.293   Median :22.67   Median :42.600  
 Mean   :2018-07-02 11:55:00   Mean   : 236.743   Mean   : 257.414   Mean   :22.84   Mean   :45.153  
 3rd Qu.:2018-10-01 17:52:30   3rd Qu.: 542.300   3rd Qu.: 533.900   3rd Qu.:26.03   3rd Qu.:59.280  
 Max.   :2018-12-31 23:50:00   Max.   :1021.000   Max.   :1348.000   Max.   :35.87   Max.   :97.700  
                               NA's   :137        NA's   :137                                        
       WS               WD              P        
 Min.   : 0.050   Min.   :  0.0   Min.   :86773  
 1st Qu.: 1.180   1st Qu.:134.7   1st Qu.:87430  
 Median : 1.785   Median :211.9   Median :87595  
 Mean   : 1.905   Mean   :210.7   Mean   :87591  
 3rd Qu.: 2.460   3rd Qu.:319.8   3rd Qu.:87761  
 Max.   :14.860   Max.   :360.0   Max.   :88517

Pre-visualizing the data:

skim(data_temixco)
── Data Summary ────────────────────────
                           Values      
Name                       data_temixco
Number of rows             52560       
Number of columns          8           
_______________________                
Column type frequency:                 
  numeric                  7           
  POSIXct                  1           
________________________               
Group variables            None        

── Variable type: numeric ───────────────────────────────────────────────────────────────────────────────────────
  skim_variable n_missing complete_rate     mean     sd       p0       p25      p50      p75    p100 hist 
1 Ib                  137         0.997   237.   328.       0        0.001     0.26   542.    1021   ▇▁▁▂▁
2 Ig                  137         0.997   257.   346.       0        0         3.29   534.    1348   ▇▁▂▂▁
3 To                    0         1        22.8    4.44     8.16    19.4      22.7     26.0     35.9 ▁▅▇▆▁
4 RH                    0         1        45.2   19.4      5.65    29.8      42.6     59.3     97.7 ▃▇▆▃▂
5 WS                    0         1         1.91   1.04     0.05     1.18      1.78     2.46    14.9 ▇▁▁▁▁
6 WD                    0         1       211.   109.       0      135.      212.     320.     360   ▃▃▆▅▇
7 P                     0         1     87591.   246.   86773.   87430.    87595.   87761.   88517.  ▁▅▇▂▁

── Variable type: POSIXct ───────────────────────────────────────────────────────────────────────────────────────
  skim_variable n_missing complete_rate min                 max                 median              n_unique
1 time                  0             1 2018-01-01 00:00:00 2018-12-31 23:50:00 2018-07-02 11:55:00    52560

Plotting one variable

ts_plot(data_temixco[c("time", "Ib", "Ig", "To", "RH")], type = "multiple", title = "Datos Temixco")
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